Context-based graphical modeling for wavelet domain signal processing

Journal Article

Wavelet-domain hidden Markov tree (HMT) modeling provides a powerful approach to capture the underlying statistics of the wavelet coefficients. We develop a mutual information-based information-theoretic approach to quantify the interactions between the wavelet coefficients within a wavelet tree. This graphical method enables the design of a context-specific hidden Markov tree (HMT) by adding or deleting links from the traditional tree structure. The performance of the model is demonstrated on segmenting two-dimensional synthetic textures having intricate substructures, although the method can be used for signals of arbitrary dimensions.

Duke Authors

Cited Authors

  • Dasgupta, N; Carin, L

Published Date

  • September 25, 2003

Published In

Volume / Issue

  • 3 /

Start / End Page

  • 485 - 488

International Standard Serial Number (ISSN)

  • 1520-6149

Citation Source

  • Scopus